ArticleComputational and structural biotechnology journal2025
AlphaFold 2, but not AlphaFold 3, predicts confident but unrealistic β-solenoid structures for repeat proteins.
Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Dye-Decolorizing Peroxidase for Lignin Depolymerization: a Comprehensive Review on Enzyme Structural Characteristics, Reaction-Influencing Factors and Efficiency-Enhancing Strategies.Applied biochemistry and biotechnology · 2026Review
- Testing the reliability of AI-generated protein structures.bioRxiv : the preprint server for biology · 2026Article
- Annotating genomes at increased scale and resolution.Nature reviews. Genetics · 2026Review
- Bridging structure and function: artificial intelligence-based modelling of kidney proteins.Nature reviews. Nephrology · 2026Review
- CsDRMH3 in tea plant (Camellia sinensis): functional study on mediating caffeine biosynthesis in relation to bud dormancy status.BMC plant biology · 2026Article
- Benchmarking TCR-pMHC structure prediction: a unified evaluation and CDR3-based functional insights.Briefings in bioinformatics · 2026Article
- Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026Review
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- The Interaction between the Tyrosine Kinase Receptor EphA2 and RNF5: Structural Insights from anComputational and structural biotechnology journal · 2026Article
- Evaluating transformer-based models for structural characterization of orphan proteins.Bioinformatics advances · 2026Article
- Structure and Disorder Predictions of Microproteins: Usage, Applications, and Pitfalls.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Fold or flop: quality assessment of AlphaFold predictions on whole proteomes.Bioinformatics advances · 2026Article
- The transformative impact of AI-enabled AlphaFold 3: evolution, current status, and future prospects in structural biology.Frontiers in artificial intelligence · 2026Review
- Designing novel solenoid proteins with in silico evolution.Communications chemistry · 2025Article
- Article
- Review
- AlphaFold3: An Overview of Applications and Performance Insights.International journal of molecular sciences · 2025Review
- ABCFold: easier running and comparison of AlphaFold 3, Boltz-1, and Chai-1.Bioinformatics advances · 2025Article
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7 authors.
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Abstract
AlphaFold 2 (AF2) has revolutionised protein structure prediction but, like any new tool, its performance on specific classes of targets, especially those potentially under-represented in its training data, merits attention. Prompted by a highly confident prediction for a biologically meaningless, randomly permuted repeat sequence, we assessed AF2 performance on sequences composed of perfect repeats of random sequences of different lengths. AF2 frequently folds such sequences into β-solenoids which, while ascribed high confidence, contain unusual and implausible features such as internally stacked and uncompensated charged residues. A number of sequences confidently predicted as β-solenoids are predicted by other advanced methods as intrinsically disordered. The instability of some predictions is demonstrated by molecular dynamics. Importantly, other deep learning-based structure prediction tools predict different structures or β-solenoids with much lower confidence suggesting that AF2 alone has an unreasonable tendency to predict confident but unrealistic β-solenoids for perfect repeat sequences. The potential implications for structure prediction of natural (near-)perfect sequence repeat proteins are also explored.
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